Deep Learning Model for Anti-Money Laundering Detection Techniques

With the growth of online payments and mobile payments in particular, an attractive environment for fraudsters is created. Changes in behavior as a result of the COVID-19 pandemic - whether the behavior of individuals, companies or governments - have in turn presented criminals with new opportunities to commit crimes and launder the proceeds. This research is based on the detection of suspicious activity transactions using machine and deep learning techniques which have potential benefits over rule based monitoring systems. The deep learning model is proposed in this research work for anti-money laundering. The proposed model is compared with other machine learning models like SVM, KNN, and Random Forest